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Computing) — Australia’s first AI-focused supercomputer in higher education. This investment will power next-generation AI and data-intensive research projects in areas such as health, climate science
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in Rail Technology – Join the IRT Team The Institute of Railway Technology (IRT) at Monash University is seeking a Senior Data Engineer to lead the design and delivery of high-performance, scalable
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of a team as well as the ability to exercise independence and judgement where required Highly developed computer literacy, including experience using business software such as Microsoft Office Strong
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technology leader to manage the transition of workstations and servers from our Malaysian Campus’ Active Directory environment into our existing corporate Active Directory. Key Responsibilities Lead the
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Nowadays more and more intelligence software solutions emerge in our daily life, for example the face recognition, smart voice assitants, and autonomous vehicle. As a type of data-driven solutions, intelligent components learn their decision logic from data corpus in an end-to-end manner and act...
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area Software Engineering The objective of this project is to design automated approach to detect bugs in various software, e.g., compilers, data libraries and so on. The project may involve LLMs
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Testing AI/LLM systems Primary supervisor Yongqiang Tian Research area Software Engineering In
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Skip to main content Main Menu - Primary Home Projects Supervisors Expression of Interest Contact Computational drug discovery Primary supervisor Geoff Webb Research area Data Science and Artificial
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leaders to align learning initiatives with strategic business goals. End-to-end program delivery – From concept to impact, you will manage programs with precision, leveraging data data to measure impact and
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of Machine Learning (ML) models across large-scale distributed systems. Leveraging advanced AI and distributed computing strategies, this project focuses on deploying ML models on real-world distributed